Some web sites and other types of interactive systems implement recommendation services for generating personalized recommendations of items stored or represented in a data repository. One common application for recommendation services involves recommending items for purchase, rental, subscription, viewing, or some other form of consumption. For example, some e-commerce sites provide services for recommending products to users based wholly or partly on the ratings assigned by the users to particular items. The recommendations may additionally or alternatively be based on the users' purchase histories, rental histories, product viewing histories, item tagging activities, and/or other behavioral profiles. Recommendation services are also commonly used to recommend web sites, news articles, music and video files, television shows, restaurants, and other types of items.
One problem with existing recommendation services is that a user's favorable rating of an item may, in certain circumstances, frequently or primarily result in recommendations of items the user dislikes. This may occur when, for example, the user likes (and thus favorably rates) a particular item, but generally dislikes the item's category. For example, a user may like a particular song or artist in the category of country music, but may generally dislike country music. A favorable item rating may also undesirably result primarily in recommendations of items the user already owns or is familiar with.